# Copyright 2022 Cerebras Systems.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import torchvision.ops as ops
from torch import nn

from modelzoo.common.pytorch.layers import (
    AdaLayerNorm,
    BatchChannelNorm2D,
    BiaslessLayerNorm,
    GroupInstanceNorm,
    RMSNorm,
)

NORM2CLASS = {
    "adalayer": AdaLayerNorm,
    "batchchannel2d": BatchChannelNorm2D,
    "batchnorm1d": nn.BatchNorm1d,
    "batchnorm2d": nn.BatchNorm2d,
    "batchnorm3d": nn.BatchNorm3d,
    "biasless-layernorm": BiaslessLayerNorm,
    "frozenbatchnorm2d": ops.FrozenBatchNorm2d,
    "group": nn.GroupNorm,
    "group_instance": GroupInstanceNorm,  # used to emulate instance norm with group norm
    "instance1d": nn.InstanceNorm1d,
    "instance2d": nn.InstanceNorm2d,
    "instance3d": nn.InstanceNorm3d,
    "layernorm": nn.LayerNorm,
    "rmsnorm": RMSNorm,
    None: nn.Identity,
}


def get_norm(norm_string):
    if norm_string is not None:
        norm_string = norm_string.lower()
    if norm_string in NORM2CLASS:
        return NORM2CLASS[norm_string]
    else:
        raise KeyError(
            f"class {norm_string} not found in NORM2CLASS mapping {list(NORM2CLASS.keys())}"
        )
